Data Science Analyst

Job Title: Data Science Analyst

Job Location: Richmond, VA (Hybrid – 1 week onsite/ 1 week Remote)

Job Duration: 12+ Months (Possibility of extension)

High Level Project Overview:

• This role serves as a technical consultant and senior individual contributor within ***’s Enterprise Data Analytics team, delivering advanced analytics and data science solutions that support operational reliability, grid modernization, customer experience, and clean energy initiatives.

Key responsibilities include:

• Partner with business units such as Generation, Transmission & Distribution, Grid Operations, Asset Management, Customer Operations, and Finance to identify high value data science use cases
• Design, build, and deploy predictive, prescriptive, and diagnostic models to support:
• Asset health and predictive maintenance
• Load forecasting and demand modeling
• Outage prediction, restoration optimization, and reliability analytics.
• Grid resilience, renewable integration, and emissions reduction initiatives.
• Customer behavior, billing, and energy efficiency programs.
• Apply advanced techniques such as time series forecasting, survival analysis, optimization, clustering, NLP, and anomaly detection to utility scale data.
• Develop end to end data science solutions, from data acquisition and feature engineering to model deployment and post production monitoring
• Support implementation of MLOps best practices to ensure scalable, reliable, and auditable analytics solutions in compliance with enterprise and regulatory standards.
• Collaborate closely with data engineers, platform teams, and cloud architects to ensure models are production ready and performant.
• Evaluate model performance continuously, identify data/model drift, and recommend retraining or enhancement strategies
• Build reusable analytical frameworks and accelerators that improve time to value across the Enterprise Analytics portfolio.
• Create intuitive visualizations, dashboards, and self service analytics tools that empower stakeholders to explore insights independently.
• Mentor junior data scientists and analysts, contributing to analytics standards, code quality, and best practices
• Support ***’s commitment to safety, reliability, affordability, and clean energy transformation through responsible and ethical use of data and AI.

Required Skills and Experience:

• MUST have prior hands on experience as a Data Scientist on a project using Python or R.
• Proven ability to translate complex analytical findings into clear, actionable insights for business leaders, engineers, operations teams, and executives
• Experience designing, developing, and deploying advanced analytics and machine learning solutions aligned to business objectives.
• Ability to create clear, interpretable visualizations that tell a compelling story, support decision making, and align with executive level messaging.
• Demonstrated experience creating interactive dashboards, reports, and applications (e.g., RShiny, Power BI, Streamlit, Dash) for business consumption
• Strong experience working with structured, semi structured, and unstructured data (e.g., sensor/SCADA data, time series data, text, images).
• Expertise across machine learning, statistical modeling, forecasting, optimization, and anomaly detection, with real world application experience.
• Experience or working knowledge of MLOps practices including model development lifecycle management, automated testing, CI/CD pipelines, version control, and deployment (e.g., MLflow, Dataiku, Azure ML, or similar tools)
• Strong understanding of model monitoring, including performance tracking, explainability, bias detection, model drift, and reproducibility in production environments.
• Experience or working knowledge of data engineering concepts, including data ingestion, transformation, feature engineering, and data quality controls.
• Experience with cloud and modern analytics platforms (AWS, Azure, GCP, Snowflake, Databricks, or similar) is a strong plus
• Understanding of governance, security, and regulatory requirements for enterprise and utility data environments is preferred.

What soft skill requirements do you have (team fit and personality requirements)?

• Strong communication skills both verbal and written.
• Ability to lead, collaborate, or work effectively in a variety of teams, including multi-disciplinary teams.

Nice to Have Skills:

• Understanding and/or Experience with data engineering is a plus.
• Experience with cloud technologies(AWS, Azure, GCP, Snowflake) is big plus.

Required Years of Experience:

• MUST have 5+ years of experience in Data Science using Python or R, with a strong focus on analyzing large, complex, and high volume datasets.

Education:

• Education: Bachelors or higher required
• Discipline: Computer Science, Information Systems, Mathematics

Are there any specific companies/industries you’d like to see in the candidate’s experience?

• High Preference for candidates that have previously worked with a large scale commercial utilities team but will review candidates who have a background with large scale capital projects for companies.

Preferred Interview Process Overview (High level):

• Teams – Camera On